# S3 Tables

Published articles for S3 Tables.

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## How Seltz cut data costs 40% with Amazon S3 Tables

DevFeed: [How Seltz cut data costs 40% with Amazon S3 Tables](<https://devfeed.tech/articles/how-seltz-cut-data-costs-40-with-amazon-s3-tables-96261.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/storage/how-seltz-cut-data-costs-40-with-amazon-s3-tables/>)

Author: Vivien de Saint Pern

Published: 2026-10-22T19:47:31Z

Content type: article

Language: en

Sources: [AWS Storage Blog](<https://devfeed.tech/sources/aws-storage-blog.md>)

Topics: [Amazon S3 Tables](<https://devfeed.tech/topics/amazon-s3-tables.md>), [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [data-engineering](<https://devfeed.tech/topics/data-engineering.md>)

Tags: [amazon](<https://devfeed.tech/tags/amazon.md>), [amazon-s3](<https://devfeed.tech/tags/amazon-s3.md>), [amazon-s3-tables](<https://devfeed.tech/tags/amazon-s3-tables.md>), [apache](<https://devfeed.tech/tags/apache.md>), [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [automatic](<https://devfeed.tech/tags/automatic.md>), [compaction](<https://devfeed.tech/tags/compaction.md>), [cost](<https://devfeed.tech/tags/cost.md>), [costs](<https://devfeed.tech/tags/costs.md>), [customer-solutions](<https://devfeed.tech/tags/customer-solutions.md>), [cut-data](<https://devfeed.tech/tags/cut-data.md>), [data](<https://devfeed.tech/tags/data.md>), [data-costs](<https://devfeed.tech/tags/data-costs.md>), [iceberg](<https://devfeed.tech/tags/iceberg.md>), [incremental](<https://devfeed.tech/tags/incremental.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [knowledge](<https://devfeed.tech/tags/knowledge.md>), [s3](<https://devfeed.tech/tags/s3.md>), [s3-tables](<https://devfeed.tech/tags/s3-tables.md>), [tables](<https://devfeed.tech/tags/tables.md>), [with](<https://devfeed.tech/tags/with.md>)

### AI overview

Seltz reports 40% lower infrastructure cost with Amazon S3 Tables than with its self-managed pipeline, based on cost modeling at its current scale; the figure excludes engineering effort. Its Knowledge Pipeline writes each enrichment stage's intermediate results to a separate Iceberg table, and a downstream indexer builds search index files. S3 Tables automatically compacts small writes and removes expired or unreferenced data, while atomic commits, independent table access, and file-level pruning support incremental processing. Seltz uses Athena for SQL monitoring and DuckDB for local inspection. The article also outlines a walkthrough using PyIceberg and Athena, requiring an AWS account with table-bucket permissions, Python 3.9+, and configured Athena.

### Source excerpt

Learn how Seltz uses Amazon S3 Tables as managed Apache Iceberg storage between the stages of its billion-document Knowledge Pipeline. The team gets automatic compaction, lifecycle management, and incremental table semantics without operating that infrastructure, cutting infrastructure cost 40 percent compared to a self-managed pipeline.

## Getting Started with S3 Tables for Apache Iceberg

DevFeed: [Getting Started with S3 Tables for Apache Iceberg](<https://devfeed.tech/articles/getting-started-with-s3-tables-for-apache-iceberg-82358.md>)

Original publisher: [Read original article](<https://estuary.dev/blog/s3-tables-for-apache-iceberg>)

Author: Dani Pálma

Published: 2024-12-05T15:31:48Z

Content type: tutorial

Language: en

Sources: [Estuary](<https://devfeed.tech/sources/estuary.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [Amazon S3 Tables](<https://devfeed.tech/topics/amazon-s3-tables.md>), [data-engineering](<https://devfeed.tech/topics/data-engineering.md>), [Apache Spark](<https://devfeed.tech/topics/spark.md>), [parquet](<https://devfeed.tech/topics/parquet.md>), [Maven](<https://devfeed.tech/topics/maven.md>)

Tags: [amazon-s3-tables](<https://devfeed.tech/tags/amazon-s3-tables.md>), [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [apache-parquet](<https://devfeed.tech/tags/apache-parquet.md>), [athena](<https://devfeed.tech/tags/athena.md>), [aws-cli](<https://devfeed.tech/tags/aws-cli.md>), [batch](<https://devfeed.tech/tags/batch.md>), [data-processing](<https://devfeed.tech/tags/data-processing.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [s3](<https://devfeed.tech/tags/s3.md>), [s3-tables](<https://devfeed.tech/tags/s3-tables.md>)

### AI overview

A step-by-step tutorial for configuring Amazon S3 Tables with Apache Iceberg, launching Spark on EMR, creating and querying Iceberg tables, and managing compaction, snapshots, and unreferenced files. It also describes how Estuary can integrate streaming and batch data into Iceberg.

### Source excerpt

Learn how to set up S3 Tables for Apache Iceberg and unlock scalable, real-time data processing with AWS. Follow this step-by-step guide to get started.